Founding Unified AI Adoption Dr. Valeriana Colón is the founder of the Unified AI Adoption Model and author of Make AI Work. Her background spans applied linguistics, organizational change, technology adoption, and education, giving her a people-centered perspective on how individuals understand, communicate about, and adopt emerging technology. She is also an Atlassian Community Champion for AI instruction, content creation, and forum facilitation. What Makes the Unified AI Adoption Model Different? The Unified AI Adoption Model (UAAM) starts with the problem and the people involved, not with a specific AI product or tool. Its approach to technology adoption predates the recent rise of large language models and is grounded in learning, behavior, organizational change, and responsible technology use. The model continues to evolve through real-world application, with resources and guidance shaped by practical challenges raised by organizations, practitioners, consultancies, and technology leaders. What Makes Connect Centric Different? Connect Centric, the official consulting partner for Unified AI Adoption, combines experienced consulting talent with the individualized attention of a smaller firm. Its focus is on delivering implementation, adoption, and measurable results—not strategy alone. Connect Centric also offers a more flexible cost structure than many large consulting firms, while its diverse leadership brings a broader global perspective to technology, people, and organizational change. Through partnerships with Atlassian, Anthropic, AWS, and other technology providers, Connect Centric also maintains current platform knowledge and meets partner capability requirements. Common Questions About AI Adoption What is AI adoption? AI adoption is the process of integrating artificial intelligence into how people and organizations work, make decisions, deliver services, and create value. It includes technology, as well as skills, processes, governance, security, measurement, and organizational support. How do I know if my organization is ready for AI? AI readiness depends on more than having the right technology. Organizations should consider leadership support, workforce skills, processes, data, security, governance, resources, and the ability to measure results. How should an organization start adopting AI? Start with a business or user problem, not with an AI tool. Identify where AI may create value, assess readiness, define ownership, choose a manageable use case, and set clear measures of success before scaling. How do you choose the right AI use cases? A strong AI use case has a clear problem, identifiable users, measurable value, acceptable risk, and enough data or information to support the work. It should also be practical to test before wider implementation. What makes AI adoption successful? Successful AI adoption connects people, business goals, technology, governance, and measurable outcomes. Organizations need both capable users and the structures required to support responsible use at scale. How do you measure ROI and business value from AI? Measure AI against the outcome it was intended to improve. Depending on the use case, this may include time saved, reduced costs, increased capacity, better quality, faster service, revenue, risk reduction, or customer outcomes. What is AI governance and when should it begin? AI governance is the system of policies, roles, controls, and oversight used to guide AI use. It should begin alongside adoption, not after AI has already spread across the organization. How do organizations move from AI pilots to scale? Before scaling, organizations should evaluate performance, security, privacy, cost, workflow fit, user readiness, governance, ownership, monitoring, and whether the AI use case continues to create enough value. How do you get employees to adopt AI responsibly? People need more than access to AI tools. They need AI literacy, practice, guidance, training, clear expectations, and support so they can use AI appropriately and know when human judgment is required. What is the difference between AI implementation and AI adoption? AI implementation focuses on putting the technology in place. AI adoption focuses on whether people can use it effectively, whether it fits the work, whether risks are managed, and whether it produces sustainable value over time.